Genome‐Wide Association Mapping of Crown Rust Resistance in Oat Elite Germplasm
Bibliographic record
Abstract
Oat crown rust, caused by f. sp. , is a major constraint to oat ( L.) production in many parts of the world. In this first comprehensive multienvironment genome-wide association map of oat crown rust, we used 2972 single-nucleotide polymorphisms (SNPs) genotyped on 631 oat lines for association mapping of quantitative trait loci (QTL). Seedling reaction to crown rust in these lines was assessed as infection type (IT) with each of 10 crown rust isolates. Adult plant reaction was assessed in the field in a total of 10 location-years as percentage severity (SV) and as infection reaction (IR) in a 0-to-1 scale. Overall, 29 SNPs on 12 linkage groups were predictive of crown rust reaction in at least one experiment at a genome-wide level of statistical significance. The QTL identified here include those in regions previously shown to be linked with seedling resistance genes , , , , , and and also with adult-plant resistance and adaptation-related QTL. In addition, QTL on linkage groups Mrg03, Mrg08, and Mrg23 were identified in regions not previously associated with crown rust resistance. Evaluation of marker genotypes in a set of crown rust differential lines supported as the identity of . The SNPs with rare alleles associated with lower disease scores may be suitable for use in marker-assisted selection of oat lines for crown rust resistance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".